Building Microservices with Spring Cloud and Docker Training Course

This instructor-led, live training in the UAE (online or onsite) is designed for engineers who wish to advance their Docker knowledge to deploy applications at a larger scale while maintaining control.

Upon completing this training, participants will be capable of:

• Creating custom Docker images.
• Deploying and managing a large number of Docker applications.
• Evaluating various container orchestration solutions and selecting the most appropriate one.
• Establishing a continuous integration workflow for Docker applications.
• Integrating Docker applications into existing continuous integration toolchains.
• Implementing security measures for Docker applications.

Docker serves as a containerization platform that facilitates consistent, portable, and reproducible environments tailored for AI and machine learning workloads.

This instructor-led live training, available online or onsite, is designed for intermediate-level professionals aiming to package ML codebases, dependencies, and models using Docker to establish reliable workflows from development to production.

Upon completion of this course, participants will be able to:

• Build and manage Docker images specifically tailored for AI and ML applications.
• Containerize machine learning pipelines, tools, and dependencies.
• Optimize Docker environments for enhanced performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Concept demonstrations supported by guided discussion.
• Hands-on exercises focused on real-world containerization tasks.
• Practical implementation utilizing live-lab Docker environments.

Course Customization Options

• To tailor this training to your organizational environment, please contact us to arrange.

CI/CD for AI represents a systematic method for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

This instructor-led live training, available online or onsite, targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows utilizing Docker and CI/CD platforms.

Upon completing the training, participants will be equipped to:

• Establish automated pipelines for constructing and testing AI model containers.
• Ensure version control and reproducibility throughout model lifecycles.
• Deploy automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations.

Course Format

• Instructor-led presentations coupled with technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations conducted in a controlled setting.

Course Customization Options

• For organizations requiring tailored pipeline workflows or specific platform integrations, please reach out to customize this course.

The Certified Kubernetes Administrator (CKA) certification program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as the premier platform for container orchestration.

Since 2015, NobleProg has been providing specialized Docker and Kubernetes training. With over 360 successfully completed training projects, we have established ourselves as one of the world's leading training providers in the field of containerization.

Since 2019, we have also been supporting our clients in validating their Kubernetes skills by preparing them to pass the CKA and CKAD exams.

This instructor-led, live training is available either online or onsite and is designed for System Administrators and Kubernetes users who wish to validate their expertise by passing the CKA exam.

Furthermore, the training emphasizes gaining practical experience in Kubernetes Administration. Therefore, we recommend participating even if you do not plan to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.
• For more information about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) program was created by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which serves as the host for Kubernetes.

This instructor-led live training, available either online or onsite, is designed for developers who want to validate their skills in designing, building, configuring, and exposing cloud-native applications for Kubernetes.

Additionally, the training emphasizes gaining practical experience in Kubernetes application development. Therefore, we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been delivering Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training companies globally in the field of containerization. Since 2019, we have also been helping our customers validate their performance in Kubernetes environments by preparing and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live training in the UAE (online or onsite) is aimed at engineers who wish to use Docker to deploy and manage software as containers instead of as traditional stand-alone software.

By the end of this training, participants will be able to:

• Install and configure Docker.
• Understand and implement software containerization.
• Managing Docker based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

In this instructor-led, live training in the UAE, participants will learn how to manage Red Hat OpenShift Container Platform.

By the end of this training, participants will be able to:

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in the public cloud, or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led live training at the UAE (onsite or remote), participants will learn how to create and manage Docker containers, followed by deploying a sample application within a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training progresses to advanced topics, guiding participants through the process of securing, scaling, and monitoring a Kubernetes cluster.

By the end of this training, participants will be able to:

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

Docker serves as a containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.

This instructor-led live training, available online or onsite, targets intermediate to advanced technical professionals seeking to containerize and operationalize complete ML pipelines using Docker.

Upon completing this training, participants will be able to:

• Containerize ML training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines utilizing Docker and supporting tools.
• Implement versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Course Format

• Interactive lectures supported by practical demonstrations.
• Hands-on exercises focused on building real ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

• For customized training aligned with specific ML infrastructure needs, please contact us to discuss options.

Course Format

• Engaging lectures combined with interactive discussions.
• Extensive exercises and practical application.
• Real-world implementation within a live laboratory environment.

Customization Options

• For tailored training on this course, please reach out to us to make arrangements.

Training Objectives: Gain theoretical and practical skills in Docker and Kubernetes.

GPU acceleration is critical for executing high-performance deep learning workloads in a scalable and efficient manner.

This instructor-led, live training (available online or onsite) is designed for intermediate-level technical professionals looking to configure, optimize, and operate GPU-enabled AI workloads within Docker containers.

Upon completing this course, participants will be able to:

• Build and execute GPU-enabled containers for both training and inference tasks.
• Configure CUDA, drivers, and runtime libraries to support containerized AI workflows.
• Optimize resource allocation and isolation for applications with heavy GPU demands.
• Deploy scalable, containerized deep learning services in production environments.

Course Format

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For tailored training aligned with your infrastructure or GPU stack, please contact us to arrange.

This instructor-led, live training in the UAE (online or onsite) targets intermediate-level Java developers who wish to design, develop, deploy, and maintain microservices-based applications using Java frameworks like Spring Boot and Spring Cloud.

By the end of this training, participants will be able to:

• Understand the principles and benefits of microservices architecture.
• Build and deploy microservices using Java and Spring Boot.
• Implement service discovery, configuration management, and API gateways.
• Secure, monitor, and scale microservices effectively.
• Deploy microservices using Docker and Kubernetes.

This instructor-led live training in the UAE (available online or onsite) is targeted at intermediate-level developers and DevOps engineers who seek to build, deploy, and manage microservices using Spring Cloud and Docker.

By the conclusion of this training, participants will be able to:

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.

This instructor-led live training in the UAE (available online or onsite) is tailored for developers seeking to transition from traditional architectures to highly concurrent, microservice-based systems using Spring Cloud, Kafka, Docker, Kubernetes, and Redis.

By the end of this training, participants will be able to:

• Configure the essential development environment for constructing microservices.
• Design and deploy a robust, highly concurrent microservices ecosystem utilizing Spring Cloud, Kafka, Redis, Docker, and Kubernetes.
• Refactor legacy monolithic and SOA services into a microservice-based architecture.
• Implement DevOps practices across the software development, testing, and release lifecycle.
• Maintain high concurrency levels for microservices in production environments.
• Monitor microservices performance and establish effective recovery strategies.
• Execute performance tuning to optimize system efficiency.
• Gain insights into emerging trends in microservices architecture.